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About

Om Ji Omer is a leading researcher at the intersection of edge computing, robotics, and 3D scene understanding, whose work is shaping the next generation of autonomous systems and augmented reality. His research focuses on three critical pillars: ultra-efficient visual-inertial odometry (VIO) for real-time pose estimation, specialized hardware acceleration for deep neural networks, and robust 3D semantic segmentation. Omer’s most cited work, “Visual Inertial Odometry At the Edge” (2019, 19 citations), introduced a groundbreaking hardware-software co-design approach that dramatically reduces latency and power consumption for VIO—a foundational requirement for AR/VR and autonomous navigation in cars, drones, and robots. He further advanced the field with “A Unified Programmable Edge Matrix Processor” (2022, 10 citations), which efficiently handles both matrix algebra and deep neural networks, and “Segment-Fusion” (2022, 10 citations), which tackles the part-misclassification problem in 3D semantic segmentation through hierarchical context fusion. His most recent work, “Ace-of-Spades” (2025), accelerates spatially sparse convolution for 3D scene understanding, promising to unlock new capabilities in robotics and autonomous driving. With a total of over 40 citations and a clear trajectory toward practical, low-power edge AI, Omer is a rising star whose innovations are directly enabling the next wave of intelligent, autonomous systems.